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Found 28 Skills
Review code architecture for maintainability, catch structural issues before they become debtUse when "Reviewing pull requests with structural changes, Planning refactoring work, Evaluating new feature architecture, Assessing technical debt, Before major releases, When code feels "hard to change", architecture, code-review, refactoring, design-patterns, technical-debt, dependencies, maintainability" mentioned.
Guides Tailwind CSS v4 patterns for buttons and components. Use this skill when creating components with variants, choosing between CVA/tailwind-variants, or configuring Tailwind v4's CSS-first approach.
Guides when to abstract vs duplicate code. Use this skill when creating shared utilities, deciding between DRY/WET approaches, or refactoring existing abstractions.
SOLID principles for clean code design and architecture
Game code architecture, design patterns, scalable systems, and maintainable code structure for complex games.
Invoke IMMEDIATELY via python script when user requests codebase understanding, architecture comprehension, or repository orientation. Do NOT explore first - the script orchestrates exploration.
Maps and documents codebases of any size by orchestrating parallel subagents. Creates docs/CODEBASE_MAP.md with architecture, file purposes, dependencies, and navigation guides. Updates CLAUDE.md with a summary. Use when user says "map this codebase", "cartographer", "/cartographer", "create codebase map", "document the architecture", "understand this codebase", or when onboarding to a new project. Automatically detects if map exists and updates only changed sections.
Holistic, system-aware planning before implementing non-trivial tasks. Use when the task involves new features, architectural decisions, multi-file changes, unclear requirements, or multiple valid approaches. Triggers on "/plan", "plan this", "design an approach", "let's plan first".
Review code for architecture: module and layer boundaries, dependency direction, single responsibility, cyclic dependencies, interface stability, and coupling. Cognitive-only atomic skill; output is a findings list.
Deep analysis of GitHub repositories to understand their core architecture, design philosophy, technical decisions, and implementation patterns. This skill should be used when users provide a GitHub URL and request comprehensive understanding of the repository's structure, purpose, key abstractions, or technical approach.
Use ONLY when creating NEW registrable components in ML projects that require Factory/Registry patterns. ✅ USE when: - Creating a new Dataset class (needs @register_dataset) - Creating a new Model class (needs @register_model) - Creating a new module directory with __init__.py factory - Initializing a new ML project structure from scratch - Adding new component types (Augmentation, CollateFunction, Metrics) ❌ DO NOT USE when: - Modifying existing functions or methods - Fixing bugs in existing code - Adding helper functions or utilities - Refactoring without adding new registrable components - Simple code changes to a single file - Modifying configuration files - Reading or understanding existing code Key indicator: Does the task require @register_* decorator or Factory pattern? If no, skip this skill.
Analyze the source code of GitHub open-source repositories and generate structured analysis reports. Supports generating reports such as project architecture overview, code quality analysis, core module description, etc., and optional synchronization to Notion.